Radio communication systems include transmitting radio signal processing systems and receiving systems as well as various sources, e.g., amplifiers, which distort or interfere with radio signals being communicated by the transmitters to the receivers. This distortion or interference can alter, modify, or disrupt signal waveforms between transmission and reception.
A machine learning model receives input and generates output based on its received input and on values of model parameters.
Neural networks are machine learning models that employ one or more layers of nonlinear units to predict an output for a received input. Some neural networks include one or more hidden layers in addition to an output layer. The output of each hidden layer is used as input to other layers in the network, e.g., the next hidden layer or the output layer. Each layer of the network generates an output from a received input in accordance with current values of a respective set of parameters. These neural networks can be trained to generate predicted output.